{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Define matplotlib defaults\n",
    "plt.rcParams['figure.figsize']        = 8., 6.\n",
    "plt.rcParams['axes.labelsize']        = 18\n",
    "plt.rcParams['axes.titlesize']        = 18\n",
    "plt.rcParams['xtick.top']             = True\n",
    "plt.rcParams['xtick.bottom']          = True\n",
    "plt.rcParams['ytick.left']            = True\n",
    "plt.rcParams['ytick.right']           = True\n",
    "plt.rcParams['xtick.direction']       = 'in'\n",
    "plt.rcParams['ytick.direction']       = 'in'\n",
    "plt.rcParams['xtick.labelsize']       = 14\n",
    "plt.rcParams['ytick.labelsize']       = 14\n",
    "plt.rcParams['xtick.major.pad']       = 6.\n",
    "plt.rcParams['xtick.minor.pad']       = 6.\n",
    "plt.rcParams['ytick.major.pad']       = 6.\n",
    "plt.rcParams['ytick.minor.pad']       = 6.\n",
    "plt.rcParams['xtick.major.size']      = 6. # major tick size in points\n",
    "plt.rcParams['xtick.minor.size']      = 3. # minor tick size in points\n",
    "plt.rcParams['ytick.major.size']      = 6. # major tick size in points\n",
    "plt.rcParams['ytick.minor.size']      = 3. # minor tick size in points\n",
    "plt.rcParams['text.usetex']           = False\n",
    "plt.rcParams['font.family']           = 'serif'\n",
    "plt.rcParams['font.size']             = 18\n",
    "\n",
    "pd.set_option('display.max_columns', None)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "# LSUN256"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "experiment_prefix = 'LSUN256'\n",
    "# Load results\n",
    "df = pd.read_csv(f'../data/{experiment_prefix.lower()}.csv')\n",
    "models = df.model.unique().tolist()\n",
    "print(df.shape)\n",
    "df.head()"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "(202, 10)\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>model</th>\n",
       "      <th>num_correct</th>\n",
       "      <th>err_rt</th>\n",
       "      <th>f_err_rt</th>\n",
       "      <th>r_err_rt</th>\n",
       "      <th>r_ans_rt</th>\n",
       "      <th>resp_time</th>\n",
       "      <th>f_resp_time</th>\n",
       "      <th>r_resp_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>participant_0</td>\n",
       "      <td>admnet-dropout</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0.405</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.585</td>\n",
       "      <td>306.91</td>\n",
       "      <td>152.06</td>\n",
       "      <td>154.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>participant_1</td>\n",
       "      <td>admnet-dropout</td>\n",
       "      <td>117.0</td>\n",
       "      <td>0.415</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.435</td>\n",
       "      <td>257.88</td>\n",
       "      <td>116.78</td>\n",
       "      <td>141.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>participant_2</td>\n",
       "      <td>admnet-dropout</td>\n",
       "      <td>142.0</td>\n",
       "      <td>0.290</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.510</td>\n",
       "      <td>333.77</td>\n",
       "      <td>162.47</td>\n",
       "      <td>171.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>participant_3</td>\n",
       "      <td>admnet-dropout</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.410</td>\n",
       "      <td>214.49</td>\n",
       "      <td>103.45</td>\n",
       "      <td>111.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>participant_4</td>\n",
       "      <td>admnet-dropout</td>\n",
       "      <td>163.0</td>\n",
       "      <td>0.185</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.555</td>\n",
       "      <td>468.61</td>\n",
       "      <td>225.07</td>\n",
       "      <td>243.53</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              id           model  num_correct  err_rt  f_err_rt  r_err_rt  \\\n",
       "0  participant_0  admnet-dropout        119.0   0.405      0.49      0.32   \n",
       "1  participant_1  admnet-dropout        117.0   0.415      0.35      0.48   \n",
       "2  participant_2  admnet-dropout        142.0   0.290      0.30      0.28   \n",
       "3  participant_3  admnet-dropout        110.0   0.450      0.36      0.54   \n",
       "4  participant_4  admnet-dropout        163.0   0.185      0.24      0.13   \n",
       "\n",
       "   r_ans_rt  resp_time  f_resp_time  r_resp_time  \n",
       "0     0.585     306.91       152.06       154.84  \n",
       "1     0.435     257.88       116.78       141.10  \n",
       "2     0.510     333.77       162.47       171.30  \n",
       "3     0.410     214.49       103.45       111.04  \n",
       "4     0.555     468.61       225.07       243.53  "
      ]
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "columns = df.columns.tolist()[3:]\n",
    "df_results = pd.DataFrame(columns=columns)\n",
    "df_results_sem = pd.DataFrame(columns=columns)\n",
    "for j, model in enumerate(models):\n",
    "    model_res = df.loc[df['model'] == model]\n",
    "    df_results.loc[model] = model_res.mean(numeric_only=True)\n",
    "    df_results_sem.loc[model] = model_res.sem(numeric_only=True) # standard error of the mean\n",
    "\n",
    "df_results"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>err_rt</th>\n",
       "      <th>f_err_rt</th>\n",
       "      <th>r_err_rt</th>\n",
       "      <th>r_ans_rt</th>\n",
       "      <th>resp_time</th>\n",
       "      <th>f_resp_time</th>\n",
       "      <th>r_resp_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>admnet-dropout</th>\n",
       "      <td>0.387000</td>\n",
       "      <td>0.440400</td>\n",
       "      <td>0.333600</td>\n",
       "      <td>0.553400</td>\n",
       "      <td>305.521600</td>\n",
       "      <td>146.537600</td>\n",
       "      <td>158.982000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ct2</th>\n",
       "      <td>0.155200</td>\n",
       "      <td>0.179200</td>\n",
       "      <td>0.131200</td>\n",
       "      <td>0.524000</td>\n",
       "      <td>325.099200</td>\n",
       "      <td>161.208800</td>\n",
       "      <td>163.888400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>diffusion-projected-gan</th>\n",
       "      <td>0.148269</td>\n",
       "      <td>0.166923</td>\n",
       "      <td>0.129615</td>\n",
       "      <td>0.518654</td>\n",
       "      <td>334.649231</td>\n",
       "      <td>146.002692</td>\n",
       "      <td>188.646154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ddpm</th>\n",
       "      <td>0.267400</td>\n",
       "      <td>0.276000</td>\n",
       "      <td>0.258800</td>\n",
       "      <td>0.508600</td>\n",
       "      <td>353.783200</td>\n",
       "      <td>176.193200</td>\n",
       "      <td>177.588800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iddpm</th>\n",
       "      <td>0.297000</td>\n",
       "      <td>0.330800</td>\n",
       "      <td>0.263200</td>\n",
       "      <td>0.533800</td>\n",
       "      <td>335.946000</td>\n",
       "      <td>164.400800</td>\n",
       "      <td>171.547200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>projected-gan</th>\n",
       "      <td>0.142000</td>\n",
       "      <td>0.140400</td>\n",
       "      <td>0.143600</td>\n",
       "      <td>0.498400</td>\n",
       "      <td>265.526400</td>\n",
       "      <td>126.664800</td>\n",
       "      <td>138.861200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylegan</th>\n",
       "      <td>0.216538</td>\n",
       "      <td>0.253846</td>\n",
       "      <td>0.179231</td>\n",
       "      <td>0.537308</td>\n",
       "      <td>427.095000</td>\n",
       "      <td>202.390769</td>\n",
       "      <td>224.704231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unleashing-transformers</th>\n",
       "      <td>0.209000</td>\n",
       "      <td>0.240400</td>\n",
       "      <td>0.177600</td>\n",
       "      <td>0.531400</td>\n",
       "      <td>305.339200</td>\n",
       "      <td>152.275600</td>\n",
       "      <td>153.063200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           err_rt  f_err_rt  r_err_rt  r_ans_rt   resp_time  \\\n",
       "admnet-dropout           0.387000  0.440400  0.333600  0.553400  305.521600   \n",
       "ct2                      0.155200  0.179200  0.131200  0.524000  325.099200   \n",
       "diffusion-projected-gan  0.148269  0.166923  0.129615  0.518654  334.649231   \n",
       "ddpm                     0.267400  0.276000  0.258800  0.508600  353.783200   \n",
       "iddpm                    0.297000  0.330800  0.263200  0.533800  335.946000   \n",
       "projected-gan            0.142000  0.140400  0.143600  0.498400  265.526400   \n",
       "stylegan                 0.216538  0.253846  0.179231  0.537308  427.095000   \n",
       "unleashing-transformers  0.209000  0.240400  0.177600  0.531400  305.339200   \n",
       "\n",
       "                         f_resp_time  r_resp_time  \n",
       "admnet-dropout            146.537600   158.982000  \n",
       "ct2                       161.208800   163.888400  \n",
       "diffusion-projected-gan   146.002692   188.646154  \n",
       "ddpm                      176.193200   177.588800  \n",
       "iddpm                     164.400800   171.547200  \n",
       "projected-gan             126.664800   138.861200  \n",
       "stylegan                  202.390769   224.704231  \n",
       "unleashing-transformers   152.275600   153.063200  "
      ]
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "df_results_sem"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>err_rt</th>\n",
       "      <th>f_err_rt</th>\n",
       "      <th>r_err_rt</th>\n",
       "      <th>r_ans_rt</th>\n",
       "      <th>resp_time</th>\n",
       "      <th>f_resp_time</th>\n",
       "      <th>r_resp_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>admnet-dropout</th>\n",
       "      <td>0.019923</td>\n",
       "      <td>0.021890</td>\n",
       "      <td>0.027337</td>\n",
       "      <td>0.014707</td>\n",
       "      <td>16.642125</td>\n",
       "      <td>8.080783</td>\n",
       "      <td>9.307364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ct2</th>\n",
       "      <td>0.021648</td>\n",
       "      <td>0.027373</td>\n",
       "      <td>0.026333</td>\n",
       "      <td>0.015898</td>\n",
       "      <td>32.447377</td>\n",
       "      <td>18.178800</td>\n",
       "      <td>16.724197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>diffusion-projected-gan</th>\n",
       "      <td>0.018794</td>\n",
       "      <td>0.023296</td>\n",
       "      <td>0.018485</td>\n",
       "      <td>0.009432</td>\n",
       "      <td>24.976251</td>\n",
       "      <td>9.722358</td>\n",
       "      <td>19.376277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ddpm</th>\n",
       "      <td>0.021292</td>\n",
       "      <td>0.020801</td>\n",
       "      <td>0.026162</td>\n",
       "      <td>0.010257</td>\n",
       "      <td>50.884233</td>\n",
       "      <td>29.902477</td>\n",
       "      <td>23.073641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iddpm</th>\n",
       "      <td>0.021422</td>\n",
       "      <td>0.028307</td>\n",
       "      <td>0.024561</td>\n",
       "      <td>0.015600</td>\n",
       "      <td>30.212193</td>\n",
       "      <td>16.001572</td>\n",
       "      <td>15.474743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>projected-gan</th>\n",
       "      <td>0.017571</td>\n",
       "      <td>0.017306</td>\n",
       "      <td>0.021946</td>\n",
       "      <td>0.009045</td>\n",
       "      <td>20.788492</td>\n",
       "      <td>9.985223</td>\n",
       "      <td>11.809294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylegan</th>\n",
       "      <td>0.018416</td>\n",
       "      <td>0.024533</td>\n",
       "      <td>0.017400</td>\n",
       "      <td>0.010638</td>\n",
       "      <td>70.967153</td>\n",
       "      <td>33.390340</td>\n",
       "      <td>38.150250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unleashing-transformers</th>\n",
       "      <td>0.022232</td>\n",
       "      <td>0.026873</td>\n",
       "      <td>0.024120</td>\n",
       "      <td>0.012558</td>\n",
       "      <td>31.765414</td>\n",
       "      <td>16.378699</td>\n",
       "      <td>15.623134</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           err_rt  f_err_rt  r_err_rt  r_ans_rt  resp_time  \\\n",
       "admnet-dropout           0.019923  0.021890  0.027337  0.014707  16.642125   \n",
       "ct2                      0.021648  0.027373  0.026333  0.015898  32.447377   \n",
       "diffusion-projected-gan  0.018794  0.023296  0.018485  0.009432  24.976251   \n",
       "ddpm                     0.021292  0.020801  0.026162  0.010257  50.884233   \n",
       "iddpm                    0.021422  0.028307  0.024561  0.015600  30.212193   \n",
       "projected-gan            0.017571  0.017306  0.021946  0.009045  20.788492   \n",
       "stylegan                 0.018416  0.024533  0.017400  0.010638  70.967153   \n",
       "unleashing-transformers  0.022232  0.026873  0.024120  0.012558  31.765414   \n",
       "\n",
       "                         f_resp_time  r_resp_time  \n",
       "admnet-dropout              8.080783     9.307364  \n",
       "ct2                        18.178800    16.724197  \n",
       "diffusion-projected-gan     9.722358    19.376277  \n",
       "ddpm                       29.902477    23.073641  \n",
       "iddpm                      16.001572    15.474743  \n",
       "projected-gan               9.985223    11.809294  \n",
       "stylegan                   33.390340    38.150250  \n",
       "unleashing-transformers    16.378699    15.623134  "
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "plt.errorbar(df_results.index, df_results.err_rt, yerr=df_results_sem.err_rt, fmt='o', capsize=5)\n",
    "plt.ylabel(\"Error Rate\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(experiment_prefix.upper())\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../plots/{experiment_prefix}_err_rt.png', bbox_inches=None, pad_inches=0.0)\n",
    "\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "plt.errorbar(df_results.index, df_results.f_err_rt, yerr=df_results_sem.f_err_rt, fmt='o', capsize=5)\n",
    "plt.ylabel(\"Error Rate on Fakes\", fontsize=14)\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(experiment_prefix)\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../plots/{experiment_prefix}_f_err_rt.png', bbox_inches=None, pad_inches=0.0)\n",
    "\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "plt.errorbar(df_results.index, df_results.r_err_rt, yerr=df_results_sem.r_err_rt, fmt='o', capsize=5)\n",
    "plt.ylabel(\"Error Rate on Reals\", fontsize=14)\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(experiment_prefix)\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../plots/{experiment_prefix}_r_err_rt.png', bbox_inches=None, pad_inches=0.0)\n",
    "\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.10.9 64-bit ('fd-ssl': conda)"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "interpreter": {
   "hash": "0b1e6c53afa0da9f8cf13ec959cb92ccd28c62ee93b35961fe33938d6192a4ab"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}